Andy Pimentel chairs the Parallel Computing Systems (PCS) group within the Systems and Networking Lab at the Informatics Institute of the University of Amsterdam. The PCS group performs research on the design, programming and run-time management of multi-core and multi-processor computer systems. The modeling, analysis and optimization of the extra-functional aspects of these systems, such as performance, power/energy consumption and system dependability but also the degree of productivity to design and program these systems, play a pivotal role in our work.
PhD in Computer Science, 1998
University of Amsterdam
MSc in Computer Science, 1993
University of Amsterdam
The paper ‘MaCP: Minimal yet Mighty Adaptation via Hierarchical Cosine Projection’ was accepted at ACL 2025.
The paper ‘Early-Exit DNN Inference on HMPSoCs’ was accepted at IEEE EDGE ‘25.
The paper ‘CompDSE: A Methodology for Design Space Exploration of Computing Subsystems within Complex Cyber-Physical Systems’ was accepted for publication in IET Cyber-Physical Systems: Theory & Applications.
The paper ‘Rethinking Computing Systems in the Era of Climate Crisis: A Call for a Sustainable Computing Continuum’ was accepted for publication in IEEE Internet Computing.
I received IEEE CEDA Outstanding Service Recognition Award and DATE Fellow Award at DATE 2025.
The paper ‘Empowering Sustainability: Energy Labeling of Digital Services Using Simulation’ was accepted as a short paper at CCGrid 2025.
NWO Knowledge and Innovation Covenant (KIC) project on ‘Improved Secure Semiconductor Evaluation (ISSE): From Lab Techniques to Legal Frameworks’ granted.
The paper ‘Energy-Efficient QoS-Aware Scheduling for S-NUCA Many-Cores’ was accepted at ISQED 2025.
The paper ‘SSH: Sparse Spectrum Adaptation via Discrete Hartley Transformation’ was accepted at NAACL 2025.
The paper ‘PEIR: Modeling Performance in Neural Information Retrieval’ was accepted at ECIR 2025.
Two journal articles about robust, distributed deep learning were published: “EASTER: Learning to Split Transformers at the Edge Robustly”, in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems and “Model and System Robustness in Distributed CNN Inference at the Edge”, in Integration, the VLSI Journal.
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BSc level course
MSc level course
MSc level course
BSc and MSc level